Data summary
- Our data contains 2311 observations for 25 commuters and 69
commutes.
- 38 days of data
- 45 person-days
- The number of minutes of total commuting time observed per commuter
ranged from 24 to 267 with a median of 54 minutes.
- We observed 1 commute for 10 commuters (40%). We observed 2-4
commutes for 9 commuters (36%) and 5-6 commutes for 6 commuters
(24%).
# total observations
nrow(rcomm)
## [1] 2311
# total commuters
unique(rcomm$ID) %>% length()
## [1] 25
# total commutes
dplyr::select(rcomm, ID, date_local, group) %>% unique() %>% nrow()
## [1] 69
# person-days
dplyr::select(rcomm, ID, date_local) %>% unique() %>% nrow()
## [1] 45
# days
dplyr::select(rcomm, date_local) %>% unique() %>% nrow()
## [1] 38
# total minutes of obs per commuter
g1 <- group_by(rcomm, ID) %>% summarize(n=n()) %>% ungroup() %>% arrange(n)
g1 %>%
kable()
| GMU1005 |
24 |
| GMU1044 |
24 |
| GMU1042 |
25 |
| GMU1043 |
31 |
| GMU1046 |
33 |
| GMU1027 |
34 |
| GMU1022 |
36 |
| GMU1047 |
37 |
| GMU1028 |
40 |
| GMU1014 |
47 |
| GMU1038 |
50 |
| GMU1050 |
50 |
| GMU1012 |
54 |
| GMU1007 |
84 |
| GMU1016 |
94 |
| GMU1035 |
95 |
| GMU1032 |
98 |
| GMU1045 |
119 |
| GMU1040 |
129 |
| GMU1036 |
139 |
| GMU1041 |
167 |
| GMU1001 |
199 |
| GMU1026 |
209 |
| GMU1018 |
226 |
| GMU1037 |
267 |
# summary of total minutes of obs per commuter
summarize(g1, min(n), max(n), median(n), mean(n))
## # A tibble: 1 × 4
## `min(n)` `max(n)` `median(n)` `mean(n)`
## <int> <int> <int> <dbl>
## 1 24 267 54 92.4
# commutes per commuter
dplyr::select(rcomm, ID, date_local, group) %>% unique() %>% group_by(ID) %>% count() %>%
ungroup() %>% rename(commutesobs= n) %>% count(commutesobs) %>%
mutate(perc = round(100 * n/sum(n), 1)) %>% kable()
| 1 |
10 |
40 |
| 2 |
3 |
12 |
| 3 |
3 |
12 |
| 4 |
3 |
12 |
| 5 |
4 |
16 |
| 6 |
2 |
8 |
The average commute length observed was approximately 30 minutes with
commutes ranging from 15 to 99 minutes.
## # A tibble: 1 × 2
## min max
## <int> <int>
## 1 15 99
| GMU1001 |
39.80000 |
16 |
50 |
44.0 |
| GMU1005 |
24.00000 |
24 |
24 |
24.0 |
| GMU1007 |
21.00000 |
17 |
26 |
20.5 |
| GMU1012 |
54.00000 |
54 |
54 |
54.0 |
| GMU1014 |
47.00000 |
47 |
47 |
47.0 |
| GMU1016 |
31.33333 |
15 |
45 |
34.0 |
| GMU1018 |
37.66667 |
24 |
63 |
32.0 |
| GMU1022 |
36.00000 |
36 |
36 |
36.0 |
| GMU1026 |
69.66667 |
37 |
99 |
73.0 |
| GMU1027 |
34.00000 |
34 |
34 |
34.0 |
| GMU1028 |
20.00000 |
18 |
22 |
20.0 |
| GMU1032 |
32.66667 |
21 |
39 |
38.0 |
| GMU1035 |
23.75000 |
15 |
34 |
23.0 |
| GMU1036 |
27.80000 |
17 |
42 |
27.0 |
| GMU1037 |
44.50000 |
26 |
76 |
39.5 |
| GMU1038 |
25.00000 |
19 |
31 |
25.0 |
| GMU1040 |
25.80000 |
15 |
45 |
23.0 |
| GMU1041 |
33.40000 |
16 |
58 |
28.0 |
| GMU1042 |
25.00000 |
25 |
25 |
25.0 |
| GMU1043 |
31.00000 |
31 |
31 |
31.0 |
| GMU1044 |
24.00000 |
24 |
24 |
24.0 |
| GMU1045 |
29.75000 |
23 |
40 |
28.0 |
| GMU1046 |
16.50000 |
15 |
18 |
16.5 |
| GMU1047 |
37.00000 |
37 |
37 |
37.0 |
| GMU1050 |
50.00000 |
50 |
50 |
50.0 |
## # A tibble: 1 × 4
## `mean(median)` `median(mean)` `mean(mean)` `median(median)`
## <dbl> <dbl> <dbl> <dbl>
## 1 33.3 31.3 33.6 31
PM
Number of zeroes
## # A tibble: 2 × 2
## ID n
## <chr> <int>
## 1 GMU1001 29
## 2 GMU1050 3
Histogram of PM

Histogram of PM by ID

Histogram of log(PM + 0.01) by ID

Summarize
By ID
| GMU1001 |
-0.04 |
2.05 |
-4.61 |
3.09 |
2.46 |
2.84 |
0.00 |
21.87 |
| GMU1005 |
1.56 |
0.17 |
1.37 |
1.88 |
4.80 |
0.85 |
3.91 |
6.52 |
| GMU1007 |
1.17 |
0.84 |
-1.11 |
2.56 |
4.28 |
2.90 |
0.32 |
12.89 |
| GMU1012 |
0.68 |
0.15 |
0.47 |
1.06 |
1.98 |
0.32 |
1.59 |
2.88 |
| GMU1014 |
1.57 |
0.42 |
0.49 |
2.54 |
5.21 |
2.03 |
1.62 |
12.62 |
| GMU1016 |
1.79 |
0.58 |
0.84 |
3.92 |
7.42 |
7.48 |
2.30 |
50.22 |
| GMU1018 |
0.88 |
0.51 |
-1.04 |
2.32 |
2.75 |
1.64 |
0.34 |
10.12 |
| GMU1022 |
2.25 |
0.18 |
1.82 |
2.60 |
9.66 |
1.71 |
6.14 |
13.46 |
| GMU1026 |
0.75 |
0.51 |
-2.19 |
2.20 |
2.37 |
1.20 |
0.10 |
9.03 |
| GMU1027 |
1.30 |
0.30 |
0.65 |
2.08 |
3.83 |
1.35 |
1.91 |
8.03 |
| GMU1028 |
2.09 |
0.37 |
1.30 |
3.09 |
8.63 |
3.41 |
3.67 |
21.97 |
| GMU1032 |
0.44 |
0.44 |
-2.08 |
1.62 |
1.67 |
0.63 |
0.11 |
5.05 |
| GMU1035 |
1.35 |
1.27 |
-0.66 |
3.88 |
9.32 |
14.00 |
0.50 |
48.25 |
| GMU1036 |
1.45 |
0.66 |
-0.01 |
2.78 |
5.22 |
3.41 |
0.98 |
16.05 |
| GMU1037 |
1.41 |
0.73 |
0.25 |
3.17 |
5.61 |
5.49 |
1.28 |
23.73 |
| GMU1038 |
1.61 |
0.74 |
1.04 |
3.89 |
7.49 |
10.18 |
2.81 |
48.72 |
| GMU1040 |
0.70 |
0.27 |
0.30 |
2.06 |
2.09 |
0.78 |
1.34 |
7.87 |
| GMU1041 |
1.71 |
0.61 |
1.05 |
2.90 |
6.63 |
4.05 |
2.84 |
18.07 |
| GMU1042 |
1.79 |
0.29 |
1.49 |
2.36 |
6.23 |
1.88 |
4.41 |
10.54 |
| GMU1043 |
0.60 |
0.27 |
-0.02 |
1.11 |
1.88 |
0.50 |
0.97 |
3.04 |
| GMU1044 |
2.91 |
0.15 |
2.63 |
3.15 |
18.60 |
2.84 |
13.84 |
23.28 |
| GMU1045 |
0.14 |
0.24 |
-0.12 |
1.03 |
1.17 |
0.33 |
0.88 |
2.79 |
| GMU1046 |
2.35 |
0.22 |
2.00 |
2.85 |
10.76 |
2.44 |
7.36 |
17.25 |
| GMU1047 |
1.58 |
0.35 |
1.10 |
2.25 |
5.16 |
1.89 |
3.00 |
9.45 |
| GMU1050 |
0.74 |
1.46 |
-4.61 |
2.62 |
3.24 |
2.41 |
0.00 |
13.79 |
Across IDs
The average minute PM2.5 across participants was 5.5 mug/m3 ranging
from 0 to 50.2 mug/m3. In general, there was greater variability between
participants than within a participant over the commutes, though
variability was great for some participants.
| lmean |
1.41 |
1.31 |
0.71 |
| mean |
5.16 |
5.54 |
3.86 |
| sd |
2.03 |
3.06 |
3.22 |
## # A tibble: 1 × 2
## min max
## <dbl> <dbl>
## 1 0 50.2
Violin plots

Box plots

Commute summaries
Mean by commute

SD by commute

Roadiness/Road type/Speed
- Possible misclassification
Most observations (N=1215, 52.6%) were for local roads. 600
observations (26%) were on highways and 399 (17.3%) were on local
connecting roads which are XX. The remainder (N=97, 4.2%) were on ramps,
tunnels, or others.
## # A tibble: 4 × 3
## rtype n perc
## <fct> <int> <dbl>
## 1 High/SecHigh 600 26
## 2 LocalConn 399 17.3
## 3 Local 1215 52.6
## 4 Other 97 4.2


Not much difference if take mode over commute type
| High/SecHigh |
17 |
24.6 |
| LocalConn |
11 |
15.9 |
| Local |
40 |
58.0 |
| Other |
1 |
1.4 |
Roadiness
Reporting values is not so useful (standardized)

| GMU1001 |
-0.72 |
0.73 |
-2.14 |
0.62 |
| GMU1005 |
0.58 |
0.25 |
0.26 |
0.92 |
| GMU1007 |
-0.35 |
0.42 |
-1.08 |
0.30 |
| GMU1012 |
-0.78 |
0.56 |
-1.61 |
0.30 |
| GMU1014 |
0.31 |
0.17 |
-0.19 |
0.43 |
| GMU1016 |
0.55 |
0.20 |
0.17 |
0.92 |
| GMU1018 |
-0.52 |
0.72 |
-1.97 |
0.30 |
| GMU1022 |
-0.12 |
0.51 |
-1.00 |
0.62 |
| GMU1026 |
-0.34 |
1.96 |
-4.59 |
2.54 |
| GMU1027 |
0.06 |
0.37 |
-0.90 |
0.36 |
| GMU1028 |
-0.78 |
0.61 |
-1.53 |
0.44 |
| GMU1032 |
-0.67 |
0.55 |
-1.56 |
0.37 |
| GMU1035 |
0.20 |
0.80 |
-1.70 |
2.35 |
| GMU1036 |
0.23 |
0.48 |
-0.84 |
0.96 |
| GMU1037 |
0.11 |
0.69 |
-2.01 |
1.08 |
| GMU1038 |
-0.27 |
0.49 |
-1.01 |
0.45 |
| GMU1040 |
0.78 |
0.54 |
0.09 |
1.80 |
| GMU1041 |
0.78 |
0.55 |
-0.28 |
2.06 |
| GMU1042 |
-1.27 |
0.89 |
-2.41 |
0.40 |
| GMU1043 |
-0.22 |
0.60 |
-0.88 |
0.70 |
| GMU1044 |
0.59 |
0.16 |
0.30 |
0.92 |
| GMU1045 |
1.13 |
0.66 |
-0.02 |
2.27 |
| GMU1046 |
-0.35 |
0.44 |
-1.34 |
0.30 |
| GMU1047 |
0.27 |
0.54 |
-1.06 |
0.62 |
| GMU1050 |
0.30 |
0.70 |
-1.21 |
1.80 |
Speed
| 24.48 |
21.38 |
0 |
93.76 |
20.41 |
32.94 |
| GMU1001 |
23.62 |
16.71 |
0.00 |
62.53 |
22.12 |
27.23 |
| GMU1005 |
25.46 |
24.83 |
0.00 |
72.42 |
14.08 |
32.81 |
| GMU1007 |
20.32 |
14.75 |
0.00 |
50.16 |
18.03 |
24.06 |
| GMU1012 |
17.74 |
16.92 |
0.00 |
67.74 |
13.66 |
19.73 |
| GMU1014 |
6.28 |
13.26 |
0.00 |
48.15 |
0.00 |
1.82 |
| GMU1016 |
19.43 |
16.11 |
0.00 |
55.89 |
18.61 |
24.99 |
| GMU1018 |
20.88 |
18.00 |
0.00 |
58.12 |
18.47 |
32.95 |
| GMU1022 |
20.85 |
16.04 |
0.00 |
49.46 |
22.91 |
32.34 |
| GMU1026 |
48.38 |
28.47 |
0.00 |
93.76 |
57.91 |
52.99 |
| GMU1027 |
22.57 |
23.61 |
0.00 |
79.88 |
18.62 |
42.41 |
| GMU1028 |
42.06 |
21.12 |
1.97 |
68.49 |
48.74 |
33.77 |
| GMU1032 |
22.13 |
17.35 |
0.00 |
77.89 |
19.49 |
27.17 |
| GMU1035 |
30.24 |
21.82 |
0.00 |
71.64 |
31.86 |
40.30 |
| GMU1036 |
18.19 |
15.28 |
0.00 |
63.86 |
17.51 |
28.57 |
| GMU1037 |
20.26 |
15.29 |
0.00 |
57.83 |
16.66 |
23.25 |
| GMU1038 |
23.47 |
18.68 |
0.00 |
60.42 |
17.41 |
29.75 |
| GMU1040 |
14.09 |
13.31 |
0.00 |
76.30 |
10.62 |
23.89 |
| GMU1041 |
17.41 |
18.62 |
0.00 |
62.58 |
11.64 |
29.67 |
| GMU1042 |
51.88 |
19.37 |
0.46 |
70.07 |
62.75 |
26.64 |
| GMU1043 |
18.34 |
17.26 |
0.12 |
52.43 |
16.73 |
30.74 |
| GMU1044 |
29.52 |
15.80 |
3.65 |
63.16 |
29.47 |
18.25 |
| GMU1045 |
32.93 |
18.72 |
0.00 |
74.55 |
34.10 |
29.79 |
| GMU1046 |
18.57 |
20.65 |
0.00 |
91.91 |
11.71 |
18.86 |
| GMU1047 |
14.67 |
20.42 |
0.00 |
56.48 |
0.00 |
29.42 |
| GMU1050 |
38.35 |
27.83 |
0.00 |
78.38 |
34.94 |
51.36 |

## # A tibble: 69 × 3
## # Groups: ID [25]
## ID id2 maxt
## <chr> <fct> <dbl>
## 1 GMU1026 GMU10262018-11-270 98
## 2 GMU1037 GMU10372019-02-041 75
## 3 GMU1026 GMU10262018-11-290 72
## 4 GMU1018 GMU10182018-11-080 62
## 5 GMU1041 GMU10412019-02-150 57
## 6 GMU1012 GMU10122018-10-180 53
## 7 GMU1001 GMU10012018-05-091 49
## 8 GMU1050 GMU10502019-03-130 49
## 9 GMU1001 GMU10012018-05-080 48
## 10 GMU1037 GMU10372019-02-051 47
## # … with 59 more rows
## # ℹ Use `print(n = ...)` to see more rows
Weather
L1 variables: I created as 1 day lag
Variables
https://www1.ncdc.noaa.gov/pub/data/ghcn/daily/readme.txt
- PRCP = Precipitation (tenths of mm)
- SNOW = Snowfall (mm)
- TMAX = Maximum temperature (degrees C, original tenths of degrees
C)
- TMIN = Minimum temperature (degrees C, original tenths of degrees
C)
- AWND = Average daily wind speed (m/s, original tenths of meters per
second)
- wdf2, wdf5 direction of fastest wind (2 vs. 5 minutes)
(degrees)
- cat2, cat5 categorical direction of fastest wind (2 vs. 5
minutes)
EDA
| awnd |
3.76 |
1.67 |
1.00 |
9.10 |
| awndL1 |
3.41 |
1.83 |
1.00 |
9.10 |
| awndL1m |
3.69 |
1.55 |
1.45 |
8.70 |
| prcp |
29.85 |
54.79 |
0.00 |
204.23 |
| prcpL1 |
45.31 |
108.38 |
0.00 |
645.98 |
| prcpL1m |
28.48 |
71.22 |
0.00 |
328.49 |
| snow |
2.94 |
10.76 |
0.00 |
61.09 |
| snowL1 |
1.18 |
6.15 |
0.00 |
40.56 |
| snowL1m |
2.85 |
8.68 |
0.00 |
34.16 |
| tmax |
13.47 |
8.03 |
2.15 |
29.22 |
| tmaxL1 |
12.83 |
7.60 |
2.60 |
28.77 |
| tmaxL1m |
12.96 |
8.43 |
-2.02 |
30.24 |
| tmin |
3.17 |
7.24 |
-12.10 |
21.05 |
| tminL1 |
3.06 |
6.91 |
-6.72 |
21.05 |
| tminL1m |
2.54 |
7.93 |
-15.80 |
21.05 |

Snow and precipation: binary
| Precipitation |
None |
18 (40) |
| Precipitation |
Some |
27 (60) |
| Snow |
None |
40 (88.9) |
| Snow |
Some |
5 (11.1) |
By observation
| awnd |
3.51 |
1.50 |
1.00 |
9.10 |
| awndL1 |
3.39 |
1.86 |
1.00 |
9.10 |
| awndL1m |
3.53 |
1.49 |
1.45 |
8.70 |
| group |
0.41 |
0.60 |
0.00 |
2.00 |
| prcp |
35.16 |
61.77 |
0.00 |
204.23 |
| prcpL1 |
46.07 |
95.39 |
0.00 |
645.98 |
| prcpL1m |
27.03 |
64.48 |
0.00 |
328.49 |
| snow |
2.03 |
8.80 |
0.00 |
61.09 |
| snowL1 |
0.84 |
5.01 |
0.00 |
40.56 |
| snowL1m |
2.67 |
8.13 |
0.00 |
34.16 |
| tmax |
12.96 |
7.79 |
2.15 |
29.22 |
| tmaxL1 |
12.19 |
7.38 |
2.60 |
28.77 |
| tmaxL1m |
12.79 |
8.22 |
-2.02 |
30.24 |
| tmin |
2.82 |
6.82 |
-12.10 |
21.05 |
| tminL1 |
2.70 |
6.76 |
-6.72 |
21.05 |
| tminL1m |
2.27 |
7.51 |
-15.80 |
21.05 |

Snow and precipation: binary
| prcpbin |
0 |
29 |
42.0 |
| prcpbin |
1 |
40 |
58.0 |
| prcpbinL1 |
0 |
25 |
36.2 |
| prcpbinL1 |
1 |
44 |
63.8 |
| prcpbinL1m |
0 |
17 |
24.6 |
| prcpbinL1m |
1 |
52 |
75.4 |
| snowbin |
0 |
63 |
91.3 |
| snowbin |
1 |
6 |
8.7 |
| snowbinL1 |
0 |
65 |
94.2 |
| snowbinL1 |
1 |
4 |
5.8 |
| snowbinL1m |
0 |
59 |
85.5 |
| snowbinL1m |
1 |
10 |
14.5 |
Wind direction



| SE |
15 |
33.3 |
| NW |
22 |
48.9 |
| Other |
8 |
17.8 |

compare commutes

Possible multiple obs of same commute:
- GMU 1045
- GMU 1040
- GMU 1037
- GMU 1036
- GMU 1035
- GMU 1032
- GMU 1018
- GMU 1016
- GMU 1007
- GMU 1001
Daily PM

## # A tibble: 1 × 4
## `mean(daily)` `sd(daily)` `min(daily)` `max(daily)`
## <dbl> <dbl> <dbl> <dbl>
## 1 6.35 3.90 1.5 21.7
Participant characteristics
## # A tibble: 1 × 4
## `mean(age)` `sd(age)` `min(age)` `max(age)`
## <dbl> <dbl> <int> <int>
## 1 26.4 8.03 18 46
| Race |
Asian |
11 (44) |
| Race |
White only |
9 (36) |
| Race |
Other/Did not specify |
5 (20) |
| Ethnicity |
Hispanic or Latino |
2 (8) |
| Ethnicity |
Not Hispanic or Latino |
23 (92) |
| Employed |
Part-time |
7 (28) |
| Employed |
Full-time |
17 (68) |
| Education |
High school diploma or GED |
6 (24) |
| Education |
Some college or technical school |
7 (28) |
| Education |
College degree or technical school degree |
5 (20) |
| Education |
Some graduate school |
2 (8) |
| Education |
Graduate school degree or post-graduate degree |
5 (20) |
| GMUstudent |
Yes |
15 (60) |
| GMUstudent |
No |
9 (36) |
| Children |
None |
18 (72) |
| Children |
1+ |
7 (28) |